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Cancer Epidemiol Biomarkers Prev. 2012 Aug;21(8):1344-7. doi: 10.1158/1055-9965.EPI-12-0406. Epub 2012 Jun 13.

External validation of Medicare claims codes for digital mammography and computer-aided detection.

Author information

  • 1Department of Family and Community Medicine and Center for Healthcare Research and Policy, University of California, Davis, Sacramento, California 95817, USA. Joshua.fenton@ucdmc.ucdavis.edu

Abstract

BACKGROUND:

While Medicare claims are a potential resource for clinical mammography research or quality monitoring, the validity of key data elements remains uncertain. Claims codes for digital mammography and computer-aided detection (CAD), for example, have not been validated against a credible external reference standard.

METHODS:

We matched Medicare mammography claims for women who received bilateral mammograms from 2003 to 2006 to corresponding mammography data from the Breast Cancer Surveillance Consortium (BCSC) registries in four U.S. states (N = 253,727 mammograms received by 120,709 women). We assessed the accuracy of the claims-based classifications of bilateral mammograms as either digital versus film and CAD versus non-CAD relative to a reference standard derived from BCSC data.

RESULTS:

Claims data correctly classified the large majority of film and digital mammograms (97.2% and 97.3%, respectively), yielding excellent agreement beyond chance (κ = 0.90). Claims data correctly classified the large majority of CAD mammograms (96.6%) but a lower percentage of non-CAD mammograms (86.7%). Agreement beyond chance remained high for CAD classification (κ = 0.83). From 2003 to 2006, the predictive values of claims-based digital and CAD classifications increased as the sample prevalences of each technology increased.

CONCLUSION:

Medicare claims data can accurately distinguish film and digital bilateral mammograms and mammograms conducted with and without CAD.

IMPACT:

The validity of Medicare claims data regarding film versus digital mammography and CAD suggests that these data elements can be useful in research and quality improvement.

©2012 AACR.

PMID:
22695737
[PubMed - indexed for MEDLINE]
PMCID:
PMC3422017
Free PMC Article
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